In this episode, we explore how CVS Health builds its product recommendation system to deliver relevant, timely suggestions across millions of customers and thousands of products. We look at the business motivation behind personalization at CVS, and then walk through how the team uses Word2Vec, Euclidean distance, LLM-generated product summaries, and iterative refinement to improve the system step by step.

For more details, you can refer to their published tech blog, linked here for your reference: https://medium.com/cvs-health-tech-blog/enhancing-you-may-also-like-ymal-systems-using-llms-and-word2vec-0340280019d2